Empirical-Mode Decomposition With Hilbert Transform for Power-Quality Assessment

By S. Shukla, Sukumar Mishra, Bhim Singh. IEEE Transactions on Power Delivery, 2009

200 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Electrical and Electronic Engineering, Electronic, Optical and Magnetic Materials

View Paper: https://www.semanticscholar.org/paper/c0ca815007e574d02956b4837d53d9caef08dad2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. Adnan M. Abu-Mahfouz
2. Khmaies Ouahada
3. Oyeniyi Akeem Alimi

In Electrical and Electronic Engineering

1. Adnan M. Abu-Mahfouz
2. Khmaies Ouahada
3. Oyeniyi Akeem Alimi

In Electronic, Optical and Magnetic Materials

1. Adnan M. Abu-Mahfouz
2. Khmaies Ouahada
3. Oyeniyi Akeem Alimi

Citations in the corpus

• A Review of Machine Learning Approaches to Power System Security and Stability (2020, methodology): “ing algorithms such as SVM [49], [53], [55], [57], [59], DT [64], [66], K-Means [67], various ANN types including Probabilistic Neural Network (PNN) [23], [68]–[70], Feed Forward Neural Network (FFNN) [51], [61], Radial basis function network (RBFNN) [63], [67] and deep neural networks such as Convo”